Investigation of corrosion behavior of Cenosphere reinforced iron based composite coatings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the present study cenopshere was reinforced with FeCrNiC (Metco 42C) as matrix material and prepared four different feedstock powders such as FeCrNiC+0%Cenosphere, FeCrNiC+5%Cenosphere, FeCrNiC+10%Cenosphere and FeCrNiC+15%Cenosphere were coated by plasma spray technique on T22 substrate. Evaluation of the substrate and coatings potential under salt spray test was performed. Dense fog of 5% NaCl salt water was used to create a corrosive atmosphere within the chamber. The salt water's pH was kept constant at 6.5–7. The materials that underwent corrosion were examined using X-ray diffraction (XRD), and scanning electron microscopy (SEM). The FeCrNiC+15%Cenosphere and FeCrNiC+10%Cenosphere coatings exhibited reduced weight loss during a 168-h corrosion test compared to the FeCrNiC+5%Cenosphere, FeCrNiC coatings, and substrate. The excellent chemical stability and corrosion resistance of Cr 23 C 6 , SiO 2 , NiO, and Cr 2 O particles contribute to gradually avoid the formation of red rust on Fe-based coated samples with exposure approaches to 52 and 130 h. • FeCrNiC (Metco 42C) based coatings with different percentages of cenosphere such as 5, 10 and 15 were successfully developed using Plasma spray. • Coatings with 10% and 15% cenosphere revealed better corrosion resistance compared to 5% cenopshere and FeCrNiC coatings. • The phases such as Cr 23 C 6 , SiO 2 , NiO, and Cr 2 O promote to avoid the formation of red rust.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it